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Large Language Models (LLMs) have significantly impacted numerous domains, including Software Engineering (SE). Many recent publications have explored LLMs applied to various SE tasks. Nevertheless, a comprehensive understanding of the application, effects, and possible limitations of LLMs on SE is still in its early stages. To bridge this gap, we conducted a Systematic Literature Review (SLR) on LLM4SE, with a particular focus on understanding how LLMs can be exploited to optimize processes and outcomes. We selected and analyzed 395 research articles from January 2017 to January 2024 to answer four key Research Questions (RQs). In RQ1, we categorize different LLMs that have been employed in SE tasks, characterizing their distinctive features and uses. In RQ2, we analyze the methods used in data collection, pre-processing, and application, highlighting the role of well-curated datasets for successful LLM for SE implementation. RQ3 investigates the strategies employed to optimize and evaluate the performance of LLMs in SE. Finally, RQ4 examines the specific SE tasks where LLMs have shown success to date, illustrating their practical contributions to the field. From the answers to these RQs, we discuss the current state-of-the-art and trends, identifying gaps in existing research, and highlighting promising areas for future study. Our artifacts are publicly available at
https://github.com/security-pride/LLM4SE_SLR
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Academic Publication Large Language Models for Software Engineering: A Systematic Literature Review
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Large Language Models for Software Engineering: A Systematic Literature Review
Large Language Models (LLMs) have significantly impacted numerous domains, including Software Engineering (SE). Many recent publications have explored LLMs applied to various SE tasks. Nevertheless...
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What is the core focus of the research titled 'Large Language Models for Software Engineering: A Systematic Literature Review'?
This literature focuses on: Large Language Models (LLMs) have significantly impacted numerous domains, including Software Engineering (SE). Many recent publications have explored LLMs applied to various SE tasks. Nevertheless, a comprehensive understanding of the application...
Are there open-source GitHub repositories related to Large Language Models for Software Engineering: A Systematic Literature Review?
Yes, open-source projects like FreedomIntelligence/OpenClaw-Medical-Skills (The largest open-source medical AI skills library for OpenClaw🦞.) are actively building upon these concepts.
Which startups are commercializing the technology behind Large Language Models for Software Engineering: A Systematic Literature Review?
Products like Ollang DX are bringing this to market. Their focus is: The AI Language Execution Layer for Enterprise.
What other academic literature is closely related to 'Large Language Models for Software Engineering: A Systematic Literature Review'?
Yes, highly correlated activity was mapped. An entry titled 'Large Language Models for Software Engineering: A Systematic Literature Review' discusses this: Large Language Models (LLMs) have significantly impacted numerous domains, including Software Engineering (SE). Many recent publications have explo...
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Commercial Realization
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GitHubFreedomIntelligence/OpenClaw-Medical-Skills
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GitHubalvinunreal/awesome-opensource-ai
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Product HuntOllang DX
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Product HuntGoogle Gemma 4